Title
Quantifying the effectiveness of ITS in improving safety of VRUs
Author
Silla, A.
Rämä, P.
Leden, L.
van Noort, M.
de Kruijff, J.
Bell, D.
Morris, A.
Hancox, G.
Scholliers, J.
Publication year
2017
Abstract
This paper presents the results of a safety impact assessment, providing quantitative estimates of the safety impacts of ten intelligent transport systems (ITS) which were designed to improve safety, mobility and comfort of vulnerable road users (VRUs). The evaluation method originally developed to assess safety impacts of ITS for cars was now adapted for assessing safety impacts of ITS for VRUs. The main results of the assessment showed that nine ITS included in the quantitative safety impact assessment affected traffic safety in a positive way by preventing fatalities and injuries. At full penetration the highest effects were obtained for Pedestrian and Cyclists Detection System + Emergency Braking (PCDS+EBR), VRU Beacon System (VBS) and Intersection Safety (INS). The estimates for PCDS+EBR showed the maximum reduction of 7.5% on all road fatalities at full penetration, which comes down to an medium estimate of around 1,900 fatalities saved per year in the EU-28 when applying the 2012 accident data and 100% penetration rate. The results regarding future scenarios showed the highest effects in number of reduced fatalities per system in the European Union (EU)-28 in 2030 for PCDS+EBR (-200 fatalities), Blind Spot Detection (BSD) (-22 fatalities), INS (-20 fatalities) and VBS (-11 fatalities). © 2017 The Institution of Engineering and Technology.
Subject
Life
FI - Functional Ingredients
ELSS - Earth, Life and Social Sciences
Food and Nutrition
Nutrition
Healthy Living
Air navigation
Intelligent systems
Intelligent vehicle highway systems
Roads and streets
Traffic control
Blind spot detections
Detection system
Full penetration
Intelligent transport systems
Intersection safety
Penetration rates
Quantitative estimates
Traffic safety
Pedestrian safety
To reference this document use:
http://resolver.tudelft.nl/uuid:6b70e4a9-772f-411f-9a6a-829cfc3ea08b
DOI
https://doi.org/10.1049/iet-its.2016.0024
TNO identifier
762764
ISSN
1751-956X
Source
IET Intelligent Transport Systems, 11 (3), 164-172
Document type
article